Compare/Qwen3 VL 32B Instruct vs Kimi K2.5 (Reasoning)

Qwen3 VL 32B InstructvsKimi K2.5 (Reasoning)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Alibaba

Qwen3 VL 32B Instruct

Input
$0.7/M
Output
$2.8/M
Speed
78 tok/s
TTFT
1.09s
Kimi

Kimi K2.5 (Reasoning)

Input
$0.6/M
Output
$3/M
Speed
36 tok/s
TTFT
1.46s

Winner by Category

Cheaper
Kimi K2.5 (Reasoning)
Faster (tok/s)
Qwen3 VL 32B Instruct
Lower Latency
Qwen3 VL 32B Instruct
Benchmarks (4-7)
Kimi K2.5 (Reasoning)

Pricing Comparison

MetricQwen3 VL 32B InstructKimi K2.5 (Reasoning)
Input ($/M tokens)$0.7$0.6
Output ($/M tokens)$2.8$3
Cost for 1M input + 100K output tokens:
Qwen3 VL 32B Instruct$0.98
Kimi K2.5 (Reasoning)$0.90

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen3 VL 32B Instruct
78 tok/s
Kimi K2.5 (Reasoning)
36 tok/s
Time to First Token (seconds) — lower is better
Qwen3 VL 32B Instruct
1.09s
Kimi K2.5 (Reasoning)
1.46s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
17.246.8
Coding Index
15.639.5
Math Index
68.3
GPQA Diamond
67.1%87.9%
MMLU-Pro
79.1%
LiveCodeBench
51.4%
AIME 2025
68.3%
MATH-500
Humanity's Last Exam
6.3%29.4%
SciCode
30.1%49.0%
IFBench
39.2%70.2%
TerminalBench
8.3%34.8%
Qwen3 VL 32B Instruct4 wins
7 winsKimi K2.5 (Reasoning)

Frequently Asked Questions

Which is cheaper, Qwen3 VL 32B Instruct or Kimi K2.5 (Reasoning)?

Kimi K2.5 (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $1.20/M tokens vs $1.23/M for Qwen3 VL 32B Instruct.

Which model performs better on benchmarks?

Kimi K2.5 (Reasoning) wins 7 out of 12 benchmarks compared to 4 for Qwen3 VL 32B Instruct. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Qwen3 VL 32B Instruct generates tokens faster at 78 tok/s vs 36 tok/s. Qwen3 VL 32B Instruct also has lower time-to-first-token (1.09s vs 1.46s).

When should I use Qwen3 VL 32B Instruct vs Kimi K2.5 (Reasoning)?

Choose based on your priorities: Kimi K2.5 (Reasoning) for lower cost, Kimi K2.5 (Reasoning) for stronger benchmark performance, and Qwen3 VL 32B Instruct for faster generation. For latency-sensitive apps, check the TTFT comparison above.